Home and Garden: Transplanted Cottonwood Trees Show Plasticity In Leaf Hyperspectral Reflectance Across An Environmental Gradient
Jaclyn PM Corbin1,2, Rebecca J Best2,3, Hillary F Cooper2,3, Catherine A Gehring1,2, Gery Allen1,2, Thomas G Whitham1,2
1 Department of Biological Science, Northern Arizona University, Flagstaff, AZ 86011, USA; jmcorbin@nau.edu
2 Center for Adaptable Western Landscapes, Northern Arizona University, Flagstaff, AZ 86011, USA
3 School of Earth & Sustainability, Northern Arizona University, Flagstaff, AZ 86011, USA
We investigated leaf hyperspectral reflectance between wild tree populations and transplanted clones to explore the plasticity of leaf spectra and their relationship to commonly measured traits. Plant functional traits are informative yet difficult to measure at the landscape scale; we explore whether these traits are detectable using leaf spectra and if spectral signatures vary between wild and transplanted trees. In this experiment, we collected ground-based hyperspectral leaf reflectance data from wild populations of Fremont cottonwood (Populus fremontii) and compared them to clones in three reciprocally planted common gardens across this species’ range. Our questions were: Are leaf spectra plastic? Do leaf spectra reveal genetic, environmental and GxE effects on tree leaves? Lastly, is tree performance predictable using leaf reflectance? Our study revealed three major patterns. 1) Populations and genotypes vary in their plasticity. Such phenotypic differences may be due to selection by the local environment, an innate genetic predisposition for being plastic, or both. 2) Specific leaf area (SLA) can be predicted at the population and genotype level using the visible light and short-wave infrared bands. Thus, leaf spectra can serve as a surrogate for a key ecological trait. 3) Tree performance (biomass, height, and number of stems) is predictable using leaf reflectance. As such, hyperspectral data may be an important tool for monitoring wild tree population success. We conclude that leaf reflectance is a tractable method for predicting plastic traits at a landscape scale. As environmental conditions continue to rapidly shift due to global climate change, accounting for the flexibility of phenotype in response to novel extremes will allow ecologists to assess possible short and long-term fitness outcomes with more accuracy. We discuss the plasticity of leaf reflectance and its correlation with key functional traits as a robust tool to explore gene by environment interactions.